Fix stride computation for dimensions with shape 0 in ndarray

[cgarling]

Some STScI Roman L2 .asdf files produced with romanisim contain !core/ndarray nodes with a zero-length shape (e.g. the chisq/dumo arrays, shape [0, 0]) and no explicit strides key. ASDF.jl's implicit C-order stride formula (stride[i] = itemsize * prod(shape[i+1:])) collapses to zero for any outer dimension whose product includes a zero-length axis, which then failed the constructor's "strides must be positive" check.

NumPy avoids this by treating zero-length dimensions as length 1 only within the running product when computing default C-contiguous strides (PyArray_NewFromDescr). The Python asdf package relies on this. Here I reproduce that convention, and have verified it against NumPy's actual output for several representative shapes/dtypes.

I also relax the post-materialization stride sanity check in getindex: Julia's reshape/reinterpret don't preserve stride values along size-0 or size-1 axes (no adjacent elements to space apart), so the check now only compares strides for dimensions with more than one element.

I verified this patch on my local L2 .asdf files: all arrays materialize with correct shapes/dtypes, and pixel values match Python's asdf exactly (accounting for Julia's column-major vs. NumPy's row-major indexing convention).

I added regression tests in test/test-ndarray.jl covering the implicit stride computation for zero-length dimensions and materialization of a zero-size block-backed array. The rest of the tests also pass for me locally.

The comments are somewhat verbose so I'm happy if you want to cut them down to size.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 100.00%. Comparing base (fd82f70) to head (34f9a77).

Additional details and impacted files

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